Operations | Monitoring | ITSM | DevOps | Cloud

A practical guide to reducing SharePoint Online storage - trim version history, empty the recycle bins, clear the Preservation Hold Library, find your largest sites, and archive inactive content to cut the $0.20/GB overage bill.

Version history is often the biggest consumer of SharePoint storage. How automatic version limits work, why setting a limit does not trim existing versions, and the exact PowerShell to reclaim the space.

Incorporating robust security measures into feature flag management is critical to protecting sensitive data and maintaining compliance. Harness FME security features, like remote evaluations in Thin SDKs and governed AI flag cleanup, let you practice security by design and standardize solid security practices across your teams.

How to recover deleted files from the SharePoint recycle bin - both stages, restore steps, PowerShell, the 93-day limit, and how to get back files that are already gone.

A DevOps toolchain that scales is the smallest unified stack with central governance and golden paths, not the longest list. 71% of teams say context-switching drains productivity; 73% of leaders report barely any teams have golden paths (Harness). AI coding speed stresses the after-code stages where DevOps toolchain sprawl creates the biggest governance gaps. Unified platforms keep governance, verification, and rollback consistent as AI raises code volume entering the pipeline.

Until now, allocating by account name meant doing the work yourself: hand-building a custom dimension that mapped every twelve-digit AWS ID to a readable name, then maintaining it by hand in CostFormation. That mapping is fragile. Rename a definition or edit the wrong line and dashboards that depended on it quietly break. Now the account name is built in for accounts connected through AWS CUR 2.0.

I spend most of my week talking to companies about AI ROI. A few months ago, that was still a weirdly specific conversation. Now it’s everywhere. CloudZero spends a lot of time in that conversation, so I’m glad the market is talking about it. But the conversation tends to start, and stall, in the wrong place. There are two ideas I keep coming back to: That doesn’t mean developer productivity is fake. It’s very real.

There's a version of cloud strategy that looks like a decision and a version that looks like drift. Most enterprises are living the second version. AWS won an early workload because the team knew it. Azure followed the Microsoft enterprise agreement. GCP came in through a data science team that preferred its ML tooling. Nobody chose concentration; it just accumulated.

Using JFrog CLI used to come with a catch. To run a build through it, you had to put it in front of the command. For example, jf npm install instead of npm install or jf mvn package instead of mvn package per the example below: npm install → jf npm install mvn package → jf mvn package Doing that once is easy enough.